Creating organizational conditions that foster employee spirit at work
Bibliographic record
Abstract
Purpose This study sought to identify organizational factors that foster an individual's experience of spirit at work. Design/methodology/approach Ten women and three men, ranging in age from 26 to 81, who were in full‐time paid employment in a variety of occupations, and who self‐identified as having high spirit at work, participated in in‐depth, reflective interviews. Findings Inspired leadership emerged as central to influencing individual experiences of spirit at work and was strongly linked to six other organizational factors (strong organizational foundation; organizational integrity; positive workplace culture and space; sense of community among members; opportunities for personal fulfillment, continuous learning, and development; and appreciation and regard for employees and their contribution). Research limitations/implications Future research needs to investigate how each of these conditions is related to measured levels of spirit at work in a larger, representative sample, and how measured spirit at work is related to work outcomes. Practical implications Although this study did not investigate specific practices or strategies to increase spirit at work, results suggest that organizations wishing to enhance their employees' spirit at work could focus efforts on creating organizational conditions that encourage inspiring leadership and mentorship and the other six identified factors. Originality/value The paper raises awareness and highlights issues surrounding organizational factors that foster an individual's experience of spirit at work.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".